词(群论)
计算机科学
自然语言处理
人工智能
单词识别
词汇判断任务
翻译(生物学)
连接主义
语言学
语音识别
心理学
认知
人工神经网络
哲学
信使核糖核酸
基因
生物化学
神经科学
化学
阅读(过程)
作者
Ton Dijkstra,Alexander Wahl,Franka Buytenhuijs,NINO VAN HALEM,ZINA AL-JIBOURI,Marcel de Korte,STEVEN REKKÉ
标识
DOI:10.1017/s1366728918000287
摘要
The computational BIA+ model (Dijkstra & Van Heuven, 2002) has provided a useful account for bilingual word recognition, while the verbal (pre-quantitative) RHM (Kroll & Stewart, 1994) has often served as a reference framework for bilingual word production and translation. According to Brysbaert and Duyck (2010), a strong need is felt for a unified implemented account of bilingual word comprehension, lexical-semantic processing, and word production. With this goal in mind, we built a localist-connectionist model, called Multilink, which integrates basic assumptions of both BIA+ and RHM. It simulates the recognition and production of cognates (form-similar translation equivalents) and non-cognates of different lengths and frequencies in tasks like monolingual and bilingual lexical decision, word naming, and word translation production. It also considers effects of lexical similarity, cognate status, relative L2-proficiency, and translation direction. Model-to-model comparisons show that Multilink provides higher correlations with empirical data than both IA and BIA+ models.
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